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8 Feature Structures Feature Structures: Attribute-Value Structures X1 f: a g: a X2 f: a g: X2 has more information than X1 X2 is more specific than X1 X2 subsumes X1 Co-indexing can be across feature structures also

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9 Unification of feature structures Given two FS, X1 and X2 X3 = X1 U X2 where X3 is the least FG which subsumes both X1 and X2 X3 is obtained by unifying X1 and X2

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12 Top and Bottom Feature Structures We need top (t) and bottom (b) feature structures for each node, especially the internal nodes of a tree. Why? For each node we have a top and bottom view from that node– adjoining can pull apart these two views. When the derivation stops then we unify the top and bottom FS at each node. If one of these unifications fails then the derivation crashes.